Аннотації
19.06.2023
Використання програмного забезпечення допомагає мобільному роботу контролювати робочі параметри: вмикати та вимикати механізми і пристрої; стежити за показниками датчиків; виконувати різні технологічні операції (різання, зварювання, фарбування тощо); розраховувати траєкторію руху залежно від робочої поверхні тощо. Дослідження в області робототехніки свідчать про високу активність наукових робіт зі створення високоточних і енергоефективних робототехнічних систем для автономних мобільних роботів шляхом вдосконалення керуючих програм. Робота присвячена розгляду й аналізу програмного забезпечення створення керуючих програм мобільних роботів. У роботі представлено узагальнену структурну схему ієрархічної системи керування мобільним роботом, в якій відбувається децентралізоване програмне опрацювання інформації, а окремі програмно-апаратні компоненти віддалені одні від одних. При побудові системи управління мобільного робота розглядаються різні середовища програмування роботів, які представляють широкий інструментарій для створення різних моделей і систем. Розглядаються питання застосування графічних та текстових програмних середовищ з мовами програмування високого рівня. Серед програмних комплексів розглядаються середовища розробки: LabView; NXT-G; Robolab; EV3-G; MRDS; Scratch; 12Blocks; Simulink; ROBO Pro; Arduino Studio and TRIK Studio. Найпоширенішими ж мовами програмування в роботі вважаються такі: С++, Python, Pascal, JAVA та Scratch. Все програмне забезпечення аналізується за такими критеріями: математичні вирази, обчислювальна модель, інтерпретація, автономне використання, генерація коду, моделювання, налагодження, методичні посібники, безкоштовність, платформи, конструктори, ліцензія та перспективи розвитку. Серед програмного забезпечення своїми можливостями відзначаються текстові засоби EV3 та Arduino, а серед графічних – Simulink та LabView, оскільки ці програмні засоби зарекомендували себе потужними середовищами розробки з доволі універсальними підходами створення програм у мобільній робототехніці.
The use of the software allows the mobile robot to control the working parameters: turn on and off the mechanisms and devices, monitor the indicators of the sensors, perform various technological operations (cutting, welding, painting, etc.), calculate the trajectory of movement depending on the working surface, etc. Research in the field of robotics testifies to the high activity of scientific works on the creation of high-precision and energy-efficient robotic systems in general for autonomous mobile robots by improving control programs. The work is devoted to the review and analysis of the software for creating control programs for mobile robots. The work presents a generalized structural diagram of a hierarchical mobile robot control system, in which decentralized software processing of information takes place, and separate software and hardware components are remote from each other. When building a mobile robot control system, various robot programming environments are considered, which represent a wide range of tools for creating various models and systems. Moreover, the issues of using graphic and text software environments with high-level programming languages are considered. Development environments are considered among the software complexes: LabView; NXT-G; Robolab; EV3-G; MRDS; Scratch; 12Blocks; Simulink; ROBO Pro; Arduino Studio and TRIK Studio. The following are considered the most common programming languages at work: C++, Python, Pascal, JAVA and Scratch. All software is analyzed according to the following criteria: mathematical expressions, computational model, interpretation, stand-alone use, code generation, modeling, debugging, tutorials, free, platforms, designers, license and development prospects. Among the software, EV3 and Arduino text tools stand out for their capabilities, and Simulink and LabView among graphic tools, as these software tools have proven themselves to be powerful development environments with fairly universal approaches to creating programs in mobile robotics.
1. Banyasad, Omid. (2000). A Visual Programming Environment for Autonomous Robots.
2. Na, Liu, Gerasin, Oleksandr, Topalov, Andrіy & Karpechenko, Anton. (2021). Analysis of tasks of monitoring and automatic control of agricultural mobile robot. Management of Development of Complex Systems, 47, 174–179, dx.doi.org\10.32347/2412-9933.2021.47.174-179.
3. Gerasin, O. S. (2014). The analysis of features multi-purpose mobile robots. Scientific papers. Computer Technology Series, 50, 238, 25–32. [in Ukrainian].
4. Kozlov, O. V., Gerasin, O. S., Kondratenko, G. V. (2017). Complex of tasks of monitoring and automatic control of mobile robots for vertical movement. International Journal “SHIPBUILDING & MARINE INFRASTRUCTURE”, 2(8), 77–87.
5. Morozovskiy, V. T. (1970). Multi-loop automatic control systems, Moscow, Energiya Publisher, 288. [in Russian].
6. Topalov, A. M. (2022). Analysis of microelectronic digital devices for collecting, processing and transmitting data to robotic systems. Materials of the all-Ukrainian scientific and practical conference of young scientists and students "Information technologies in education, technology and industry" on October 13, Ivano-Frankivsk, 117–119.
7. Portsmore, M. (1999). ROBOLAB: Intuitive Robotic Programming Software to Support Life Long Learning. APPLE Learning Technology Review..
8. Biggs, G., MacDonald, B. (2003). A survey of robot programming systems. Proceedings of the Australasian conference on robotics and automation, P. 1–3.
9. Simpson, Jonathan, Jacobsen, Christian L., Jadud, Matthew C. (2006). Mobile robot control. Communicating Process Architectures, 225.
10. Simpson, Jonathan, Jacobsen, Christian L. (2008). Visual Process-Oriented Programming for Robotics. CPA, 365–380.
11. Posso, Jeremy C., Sampson, Adam T., Simpson, Jonathan. (2011). Process-Oriented Subsumption Architectures in Swarm Robotic Systems. CPA, 303–316.
12. Simpson, Jonathan, Ritson, Carl, Toward, G. (2009). Process Architectures for Behavioural Robotics. CPA, 375–386.
13. Brooks, Rodney [et all]. (1986). A robust layered control system for a mobile robot. Robotics and Automation, IEEE Journal, 2, 1, 14–23.
14. Connell, Jonathan H. (1989). A colony architecture for an artificial creature: Tech. Rep.: DTIC Document.
15. Arkin, Ronald C. (1987). Motor schema based navigation for a mobile robot: An approach to programming by behavior. Robotics and Automation. Proceedings. 1987 IEEE International Conference on IEEE. Т. 4. 1987. P. 264–271.
16. Rosenblatt, Julio K. (1997). DAMN: A distributed architecture for mobile navigation. Journal of Experimental & Theoretical Artificial Intelligence, 9, 2–3, 339–360.
17. Diprose, James P, MacDonald, Bruce A, Hosking, John G. (2011). Ruru: A spatial and interactive visual programming language for novice robot programming. Visual Languages and Human-Centric Computing (VL/HCC), 2011 IEEE Symposium on IEEE. 2011. P. 25–32.
18. Johnston ,Wesley M., Hanna, JR, Millar, Richard J. (2004). Advances in dataflow programming languages. ACM Computing Surveys (CSUR), 36, 1, 1–34.
19. Hils, Daniel D. (1992). Visual languages and computing survey: Data flow visual programming languages. Journal of Visual Languages & Computing, 3, 1, 69–101.
20. Powers, Kris, Gross, Paul, Cooper, Steve. (2006). Tools for teaching introductory programming: what works? ACM SIGCSE Bulletin, 38, 560–561.
21. Kodosky, Jeffrey, MacCrisken, Jack, Rymar Gary. (1991). Visual programming using structured data flow. Visual Languages, 1991, Proceedings. 1991 IEEE Workshop on / IEEE. Р. 34–39.
22. Gomez-de Gabriel, Jesús M., Mandow, Anthony, Fernandez-Lozano, Jesús. (2011). Using LEGO NXT Mobile Robots With LabVIEW for Undergraduate Courses on Mechatronics. IEEE Trans. Educ., 54, 1, 41–47.
23. Jackson, Jared. (2007). Microsoft robotics studio: A technical introduction. Robotics & Automation Magazine, IEEE, 14, 4, 82–87.
24. Kelly, James Floyd. (2010). Lego Mindstorms NXT-G Programming Guide. Apress.
25. Cyr, Martha. (2001). Robolab N. Software Reference Guide. Moscow: INT [translation].
26. Lytvynov, Yu. V., Kirylenko, Ya. A. (2015). TRIK Studio: an environment for teaching programming with the use of robots. V All-Russian conference "Modern technological education: from computer to work" (collection of theses), р. 5–7.
27. Robot Pro URL:https://apps.apple.com/ru/app/robo-pro-coding/id1569643514
28. Robot Operating System, URL: http://www.ros.org/
29. Resnick, M., Maloney, J., Monroy-Hern´andez, Scratch A. (2009). Programming for all. Communications of the ACM, 52, 11, 60–67.
30. Araujo, Hernando León, Agudelo, Jesús Gulfo, Crawford, Richard, Vidal, Jorge, Ardila, Uribe. (2022). Autonomous Mobile Robot Implemented in LEGO EV3 Integrated with Raspberry Pi to Use Android-Based Vision Control Algorithms for Human-Machine Interaction. Machines, 10(3), 193.
31. Dong, C., Povorozniuk, O., Topalov, A., Wang, K., Chen, Z. (2023). Development of the control system for LEGO Mindstorms EV3 mobile robot based on MATLAB/Simulink elements. Technology Audit and Production Reserves, 1 (2 (69)), 30–35. doi: https://doi.org/10.15587/27065448.2023.274846.
32. Oltean, S. E. (2019). Mobile Robot Platform with Arduino Uno and Raspberry Pi for Autonomous Navigation. Procedia Manufacturing, 32, 572–577.
1. Banyasad, Omid. (2000). A Visual Programming Environment for Autonomous Robots.
2. Na, Liu, Gerasin, Oleksandr, Topalov, Andrіy & Karpechenko, Anton. (2021). Analysis of tasks of monitoring and automatic control of agricultural mobile robot. Management of Development of Complex Systems, 47, 174–179, dx.doi.org\10.32347/2412-9933.2021.47.174-179.
3. Gerasin, O. S. (2014). The analysis of features multi-purpose mobile robots. Scientific papers. Computer Technology Series, 50, 238, 25–32. [in Ukrainian].
4. Kozlov, O. V., Gerasin, O. S., Kondratenko, G. V. (2017). Complex of tasks of monitoring and automatic control of mobile robots for vertical movement. International Journal “SHIPBUILDING & MARINE INFRASTRUCTURE”, 2(8), 77–87.
5. Morozovskiy, V. T. (1970). Multi-loop automatic control systems, Moscow, Energiya Publisher, 288. [in Russian].
6. Topalov, A. M. (2022). Analysis of microelectronic digital devices for collecting, processing and transmitting data to robotic systems. Materials of the all-Ukrainian scientific and practical conference of young scientists and students "Information technologies in education, technology and industry" on October 13, Ivano-Frankivsk, 117–119.
7. Portsmore, M. (1999). ROBOLAB: Intuitive Robotic Programming Software to Support Life Long Learning. APPLE Learning Technology Review..
8. Biggs, G., MacDonald, B. (2003). A survey of robot programming systems. Proceedings of the Australasian conference on robotics and automation, P. 1–3.
9. Simpson, Jonathan, Jacobsen, Christian L., Jadud, Matthew C. (2006). Mobile robot control. Communicating Process Architectures, 225.
10. Simpson, Jonathan, Jacobsen, Christian L. (2008). Visual Process-Oriented Programming for Robotics. CPA, 365–380.
11. Posso, Jeremy C., Sampson, Adam T., Simpson, Jonathan. (2011). Process-Oriented Subsumption Architectures in Swarm Robotic Systems. CPA, 303–316.
12. Simpson, Jonathan, Ritson, Carl, Toward, G. (2009). Process Architectures for Behavioural Robotics. CPA, 375–386.
13. Brooks, Rodney [et all]. (1986). A robust layered control system for a mobile robot. Robotics and Automation, IEEE Journal, 2, 1, 14–23.
14. Connell, Jonathan H. (1989). A colony architecture for an artificial creature: Tech. Rep.: DTIC Document.
15. Arkin, Ronald C. (1987). Motor schema based navigation for a mobile robot: An approach to programming by behavior. Robotics and Automation. Proceedings. 1987 IEEE International Conference on IEEE. Т. 4. 1987. P. 264–271.
16. Rosenblatt, Julio K. (1997). DAMN: A distributed architecture for mobile navigation. Journal of Experimental & Theoretical Artificial Intelligence, 9, 2–3, 339–360.
17. Diprose, James P, MacDonald, Bruce A, Hosking, John G. (2011). Ruru: A spatial and interactive visual programming language for novice robot programming. Visual Languages and Human-Centric Computing (VL/HCC), 2011 IEEE Symposium on IEEE. 2011. P. 25–32.
18. Johnston ,Wesley M., Hanna, JR, Millar, Richard J. (2004). Advances in dataflow programming languages. ACM Computing Surveys (CSUR), 36, 1, 1–34.
19. Hils, Daniel D. (1992). Visual languages and computing survey: Data flow visual programming languages. Journal of Visual Languages & Computing, 3, 1, 69–101.
20. Powers, Kris, Gross, Paul, Cooper, Steve. (2006). Tools for teaching introductory programming: what works? ACM SIGCSE Bulletin, 38, 560–561.
21. Kodosky, Jeffrey, MacCrisken, Jack, Rymar Gary. (1991). Visual programming using structured data flow. Visual Languages, 1991, Proceedings. 1991 IEEE Workshop on / IEEE. Р. 34–39.
22. Gomez-de Gabriel, Jesús M., Mandow, Anthony, Fernandez-Lozano, Jesús. (2011). Using LEGO NXT Mobile Robots With LabVIEW for Undergraduate Courses on Mechatronics. IEEE Trans. Educ., 54, 1, 41–47.
23. Jackson, Jared. (2007). Microsoft robotics studio: A technical introduction. Robotics & Automation Magazine, IEEE, 14, 4, 82–87.
24. Kelly, James Floyd. (2010). Lego Mindstorms NXT-G Programming Guide. Apress.
25. Cyr, Martha. (2001). Robolab N. Software Reference Guide. Moscow: INT [translation].
26. Lytvynov, Yu. V., Kirylenko, Ya. A. (2015). TRIK Studio: an environment for teaching programming with the use of robots. V All-Russian conference "Modern technological education: from computer to work" (collection of theses), р. 5–7.
27. Robot Pro URL:https://apps.apple.com/ru/app/robo-pro-coding/id1569643514
28. Robot Operating System, URL: http://www.ros.org/
29. Resnick, M., Maloney, J., Monroy-Hern´andez, Scratch A. (2009). Programming for all. Communications of the ACM, 52, 11, 60–67.
30. Araujo, Hernando León, Agudelo, Jesús Gulfo, Crawford, Richard, Vidal, Jorge, Ardila, Uribe. (2022). Autonomous Mobile Robot Implemented in LEGO EV3 Integrated with Raspberry Pi to Use Android-Based Vision Control Algorithms for Human-Machine Interaction. Machines, 10(3), 193.
31. Dong, C., Povorozniuk, O., Topalov, A., Wang, K., Chen, Z. (2023). Development of the control system for LEGO Mindstorms EV3 mobile robot based on MATLAB/Simulink elements. Technology Audit and Production Reserves, 1 (2 (69)), 30–35. doi: https://doi.org/10.15587/27065448.2023.274846.
32. Oltean, S. E. (2019). Mobile Robot Platform with Arduino Uno and Raspberry Pi for Autonomous Navigation. Procedia Manufacturing, 32, 572–577.